Researchers from Google and MIT published a paper describing a predictive framework for scaling multi-agent systems. The framework shows that there is a tool-coordination trade-off and it can be used

InfoQ is a leading online platform for software developers, architects, and technical leaders, providing news, articles, presentations, and interviews on a wide range of topics, including agile practices, DevOps, microservices, and emerging technologies. With a focus on quality content and expert insights, InfoQ helps professionals stay informed about the latest trends, best practices, and industry developments. Developers can learn from real-world experiences, gain  knowledge, and connect with peers in the global software community through InfoQ's diverse and engaging content.

InfoQ

Google and MIT researchers published a predictive framework for scaling multi-agent systems, identifying key factors like an LLM's intelligence index, number of agents, tools, and coordination metrics. The framework reveals three dominant effects: a tool-coordination trade-off, capability saturation, and topology-dependent error amplification. It classifies architectures as independent, centralized, decentralized, or hybrid, and predicts the optimal coordination strategy with 87% accuracy on held-out data. Notably, financial reasoning tasks benefit from centralized orchestration while web navigation favors decentralized approaches. The researchers argue that smarter foundation models accelerate the need for well-architected multi-agent systems rather than replacing them.

Google Publishes Scaling Principles for Agentic Architectures